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Analysis on the Impact Factors for the Pulling Force of the McKibben Pneumatic Artificial Muscle by a FEM Model

机译:有组织模型对麦克亨恩气动肌肉拉力的影响因素分析

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Modelling the behaviour of Pneumatic Artificial Muscle (PAM) has proven difficult due to its highly complicated structure, nonlinear nature of rubbery material, and air compressibility. To overcome these limitations, a FEM (Finite Element Method) model using Abaqus and CATIA is derived for the quantitative analysis on the impact of different factors on the pulling force of PAM. In the Abaqus a two parameter Mooney–Rivlin model is utilized to consider the hyper-elastic nature of flexible material. Then both Abaqus and CATIA are used in the parametric design of a 3-Dimensional model of PAM. Furthermore, the FEM model is employed to predict the static force exerted by PAM and the results show that the model is promising. The FEM model produces closer results to the test data for the typical PAM. Nonlinear behaviour of PAM is found to be obvious with an increase in both the contraction and the air pressure, different from the linear curves obtained by the fundamental geometrical model. Nonlinear changes in the PAM force are also observed in the numerical study on the effect of structural factors including initial braid angle, initial diameter, initial wall thickness, and flexible material. Besides, these phenomena can be explained by a connection between mechanical and morphological behaviour of PAMs with the FEM model. Generally, this modelling approach is more accurate compared to the fundamental theoretical model and more cost competitive compared to the empirical methods.
机译:模拟气动人工肌肉(PAM)的行为由于其高度复杂的结构,橡胶状材料的非线性性质和空气压缩性而难​​以实现困难。为了克服这些限制,可以推导使用ABAQUS和CATIA的FEM(有限元方法)模型用于定量分析不同因素对粉刷拉力的影响。在ABAQUS中,使用两个参数Mooney-Rivlin模型来考虑柔性材料的超弹性性质。然后,ABAQUS和CATIA都用于PAM的三维模型的参数设计。此外,采用有限元模型来预测众议局部施加的静力,结果表明该模型是有前途的。有组态模型对典型PAM的测试数据产生更接近的结果。发现PAM的非线性行为随着收缩和空气压力的增加而显而易见,与基本几何模型获得的线性曲线不同。在数值研究中也观察到PAM力的非线性变化对结构因子,初始直径,初始壁厚和柔性材料的结构因素的影响。此外,这些现象可以通过与FEM模型的PAM的机械和形态行为之间的联系来解释。通常,与实证方法相比,这种建模方法与基本理论模型相比更准确,更具成本竞争力。

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